Sound Event Detection

Sound Event Detection (SED) is the task of recognizing the sound events and their respective temporal start and end time in a recording. Sound events in real life do not always occur in isolation, but tend to considerably overlap with each other. Recognizing such overlapping sound events is referred as polyphonic SED.

Source: A report on sound event detection with different binaural features

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 61–70 of 194 papers

Title	Date	Tasks	Status	Hype
Pretraining Representations for Bioacoustic Few-shot Detection using Supervised Contrastive Learning	Sep 2, 2023	Contrastive LearningData Augmentation	CodeCode Available	1
Leveraging Language Model Capabilities for Sound Event Detection	Aug 22, 2023	DecoderEvent Detection	—Unverified	0
DiffSED: Sound Event Detection with Denoising Diffusion	Aug 14, 2023	DecoderDenoising	—Unverified	0
Post-Processing Independent Evaluation of Sound Event Detection Systems	Jun 27, 2023	Event DetectionSound Event Detection	CodeCode Available	1
Auditory Neural Response Inspired Sound Event Detection Based on Spectro-temporal Receptive Field	Jun 20, 2023	Event DetectionSound Event Detection	—Unverified	0
Channel-Spatial-Based Few-Shot Bird Sound Event Detection	Jun 18, 2023	Event DetectionFew-Shot Learning	—Unverified	0
Few-shot bioacoustic event detection at the DCASE 2023 challenge	Jun 15, 2023	Event DetectionFew-Shot Learning	CodeCode Available	1
Semi-supervsied Learning-based Sound Event Detection using Freuqency Dynamic Convolution with Large Kernel Attention for DCASE Challenge 2023 Task 4	Jun 10, 2023	Event DetectionPseudo Label	—Unverified	0
Self-supervised Audio Teacher-Student Transformer for Both Clip-level and Frame-level Tasks	Jun 7, 2023	Audio ClassificationAudio Tagging	CodeCode Available	1
Divided spectro-temporal attention for sound event localization and detection in real scenes for DCASE2023 challenge	Jun 5, 2023	Event DetectionSound Event Detection	—Unverified	0

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All datasets DESED L3DAS21 WildDESED Mivia Audio Events Mivia Road Events

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	ATST-SED	event-based F1 score	63.4	—	Unverified
2	SE-CRNN-16 with DualKD	event-based F1 score	55.6	—	Unverified
3	FDY-CRNN	event-based F1 score	54	—	Unverified
4	HTS-AT	event-based F1 score	50.7	—	Unverified
5	RCT	event-based F1 score	49.62	—	Unverified
6	FiltAug SED	event-based F1 score	49.6	—	Unverified
7	SED-SSep baseline dcase task 4 2020 v2	event-based F1 score	40.7	—	Unverified
8	Baseline dcase task 4 2020 v2	event-based F1 score	39	—	Unverified
9	Baseline	event-based F1 score	25.8	—	Unverified
10	MAT-SED	PSDS1	0.59	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	PHC SEDnet n=8	Error Rate	0.56	—	Unverified
2	Quaternion SEDnet	Error Rate	0.52	—	Unverified
3	PHC SEDnet n=16	Error Rate	0.51	—	Unverified
4	PHC SEDnet n=4	Error Rate	0.45	—	Unverified
5	PHC SEDnet n=2	Error Rate	0.39	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CRNN (with BEATs + Separation)	PSDS1 (-5dB)	0.13	—	Unverified
2	CRNN (with BEATs)	PSDS1 (-5dB)	0.07	—	Unverified
3	CRNN (WildDESED + Curriculrm learning)	PSDS1 (-5dB)	0.05	—	Unverified
4	CRNN (WildDESED)	PSDS1 (-5dB)	0.05	—	Unverified
5	CRNN	PSDS1 (-5dB)	0.02	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DENet	Rank-1 Recognition Rate	0.98	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DENet	Rank-1 Recognition Rate	1	—	Unverified